Joel Wesson

Wind speed effect on L-band brightness temperature inferred from EuroSTARRS and WISE 2001 field experiments

The results from two field experiments in the Mediterranean Sea are used to study the wind speed dependence of brightness temperature at L-band. During the EuroSTARRS airborne experiment, an L-band radiometer made measurements across a large wind speed gradient, enabling us to study this dependence at high wind speed. We compare our results with a two-scale emissivity model using several representations of the sea state spectrum. While the results are encouraging, unfortunately the accuracy of the measurements does not permit us to distinguish between the so-called twice Durden and Vesecky spectrum and the Elfouhaily spectrum above 7 m/spl middot/s/sup -1/. The effect of foam is certainly small. During the WISE 2001 field experiment carried on an oil rig, we studied this dependence at low wind speed, finding an abrupt decrease of the wind speed effect on the brightness temperature below 3 m/spl middot/s/sup -1/.

Ocean Surface Roughness Spectrum in High Wind Condition for Microwave Backscatter and Emission Computations

AbstractOcean surface roughness plays an important role in air–sea interaction and ocean remote sensing. Its primary contribution is from surface waves much shorter than the energetic wave components near the peak of the wave energy spectrum. Field measurements of short-scale waves are scarce. In contrast, microwave remote sensing has produced a large volume of data useful for short-wave investigation. Particularly, Bragg resonance is the primary mechanism of radar backscatter from the ocean surface and the radar serves as a spectrometer of short surface waves. The roughness spectra inverted from radar backscatter measurements expand the short-wave database to high wind conditions in which in situ sensors do not function well. Using scatterometer geophysical model functions for L-, C-, and Ku-band microwave frequencies, the inverted roughness spectra, covering Bragg resonance wavelengths from 0.012 to 0.20 m, show a convergent trend in high winds. This convergent trend is incorporated in the surface rough...

Deriving Sea Surface Salinity and Density Variations From Satellite and Aircraft Microwave Radiometer Measurements: Application to Coastal Plumes Using STARRS

Using brightness temperature Tb measurements from L-band airborne microwave radiometers, with independent sea surface temperature (SST) observations, sea surface salinity (SSS) can be remotely determined with errors of about 1 psu in temperate regions. Nonlinearities in the relationship between Tb, SSS, and SST produce variations in the sensitivity of salinity S to variations in Tb and SST. Despite significant efforts devoted to SSS remote sensing retrieval algorithms, little consideration has been given to deriving density D from remotely sensed SSS and SST. Density is related to S and T through the equation of state. It affects the oceans static stability and its dynamical response to forcings. By chaining together two empirical relationships (flat-sea emissivity and equation of state) to form an inversion algorithm for sea surface density (SSD) in terms of Tb and SST, we develop a simple L-band SSD retrieval algorithm. We use this to investigate the sensitivity of SSD retrievals to observed Tb and SST and infer errors in D for typical sampling configurations of the airborne Salinity, Temperature, And Roughness Remote Scanner (STARRS) and satellite-borne Soil Moisture and Ocean Salinity (SMOS) and Aquarius radiometers. We then derive D from observations of river plumes obtained using STARRS and demonstrate several oceanographic applications: the observations are used to study variations in T and S effects on D in the Mississippi plume, and the across-shelf density gradient is used to infer surface geostrophic shear and subsurface geostrophic current in the Plata plume. Future basin-scale applications of SSD retrievals from satellite-borne microwave radiometers such as SMOS and Aquarius are anticipated.

Optimizing Performance of a Microwave Salinity Mapper: STARRS L-Band Radiometer Enhancements*

Abstract Airborne microwave radiometers for salinity remote sensing have advanced to a point where operational surveys can be conducted over the inner continental shelf to observe the evolution of freshwater plumes emanating from rivers and estuaries. To determine seawater microwave emissivity, and hence conductivity and salinity, precisely and accurately demands high instrument sensitivity, stability, and sampling rates; such requirements involve significant design trade-offs. The Salinity, Temperature, and Roughness Remote Scanner (STARRS) was developed to enhance these features relative to existing instruments. The authors describe here key elements of the STARRS design and the results of early performance assessments and deployments. During early deployments, the instrument performed well in areas of moderate to high salinity signal-to-noise ratio, but more homogenous areas revealed band-limited random signal fluctuations on the order of a 6-min period and ∼1-K amplitude that were of internal origin. ...

Observing sea surface salinity in coastal domains using an airborne surface salinity mapper

Sea Surface Salinity directly affects the status of coastal ecosystems and serves as a tracer for seawater constituents associated with freshwater runoff. As part of an NRL-sponsored study of the dynamics of coastal buoyancy jets (CoJet), which began in July, 2000, the original Scanning Low Frequency Microwave Radiometer (SLFMR) was deployed in various coastal locations to evaluate its performance for mapping sea surface salinity, and demonstrate its application to studies of coastal plumes and buoyant jets. In a sequence of three campaigns, the radiometer was flown repeatedly over the Cheseapeake and Mobile Bay plumes and over the northern Gulf of Mexico and Florida Bay using a twin-engine Piper Navajo aircraft. Extensive surveys of sea surface salinity distributions were conducted on time scales of a few hours. The instrument was field calibrated using in situ data from oceanographic research vessels and the resulting salinity maps were corrected for known environmental influences. The logistical convenience and broad dynamic range of the instrument allowed surface maps to be generated quickly over waters that were either significantly fresher or more saline than standard seawater. The instrument performance and resulting map quality were thus found to meet the requirements of coastal oceanographic studies that are characterized by large buoyancy signals, and a variety of forcing effects that evolve relatively rapidly in time and space. The instrument and data processing system are first described and two new methods of field calibration method are presented. Examples of surface salinity maps of rapidly evolving coastal plume features are then described and interpreted using supporting in situ data. Finally, the overall capability and utility of the system is evaluated, and recent advances in the technology and future prospects are briefly considered.

An Advanced Roughness Spectrum for Computing Microwave L-Band Emissivity in Sea Surface Salinity Retrieval

The influence of sea surface roughness dominates the error budget of satellite sea surface salinity (SSS) retrieval from L-band radiometers; thus, accurate roughness correction models are needed. Semi-analytical SSS correction models, as used in the soil moisture and ocean salinity satellite Level 2 processor, combine an emissivity model with an ocean wave spectrum model that describes the rough sea surface. Previous findings indicate that the errors contributed by ocean roughness model exceed those of the emissivity model. In this paper, we compare the performance of three well-known spectrum models and a new one as inputs to the small slope approximation/small perturbation method emissivity model. The new spectrum model, which is developed from empirical parameterization of short water wave spectra measured in the ocean and incorporates swell effects, performs very well in comparison with the other spectrum models, and we propose its consideration for future SSS roughness correction models.

Aircraft and in Situ Salinity and Ocean Color Measurements and Comparisons in the Gulf of Mexico

We report here on aircraft measurements made in May, 2007, with the NRL STARRS (Salinity, Temperature and Roughness Remote Scanner), and optical multi-wavelength radiance and irradiance sensors (Satlantic OCR-507 at SEA-WIFS wavelength bands). These measurements were made in conjunction with in situ measurements of sea surface salinity (SSS), ocean color, and fluorescence in the Atchafalaya River outflow from the R/V Pelican. In this work we demonstrate the ability of the aircraft optical and L-Band measurements to (a) detect the location of salinity and color fronts as observed in the in situ measurements from the ship and (b) provide context for the in situ measurements by providing synoptic measurements over a wider area than the ship was able to cover. A multilinear regression for salinity, based on three of the optical channels, provides an excellent qualitatative proxy for large scale salinity in the Atchafalaya plume region. We believe this is the first simultaneous use of L-Band and optical instruments to measure salinity from an aircraft.

Relationship between sea surface salinity from L-band radiometer and optical features in the East China Sea

The East China Sea (ECS) is often obscured from space in the visible and near-visible bands by cloud cover, which prevents remote sensing retrieval of optical properties. However, clouds are transparent to microwaves, and satellites with L-band radiometers have recently been put into orbit to monitor sea surface salinity (SSS). Previous studies have used the mixing of fluvial colored dissolved organic matter (CDOM) near coasts, where the mixing is approximately conservative over short time scales, to estimate SSS. In this study, the usual relationship between CDOM and salinity in the ECS has been used in reverse to estimate CDOM from remotely sensed SSS in the ECS and compare that CDOM with MODIS data. The SSS data used are 7 day composites from NASA’s Aquarius/SAC-D satellite which has an L-band radiometer. The challenges in using this approach are that 1) Aquarius SSS has coarse spatial resolution (150 km), and 2) the ECS has numerous anthropogenic sources of radiofrequency interference which adds noise to the L-band signal for the SSS retrievals. Despite the limits in the method, CDOM distribution in the ECS can be estimated under cloudy conditions. In addition to all-weather retrievals, an additional advantage of the approach is that the algorithm provides an estimate of CDOM absorption that is unaffected by the spectrally similar detritus absorption that can confound optical remote sensing estimates of CDOM.

Sea surface signature of tropical cyclones using microwave remote sensing

Measuring the sea surface during tropical cyclones (TC) is challenging due to severe weather conditions that prevent shipboard measurements and clouds which mask the sea surface for visible satellite sensors. However, sea surface emission in the microwave L-band can penetrate rain and clouds and be measured from space. The European Space Agency (ESA) MIRAS L-band radiometer on the Soil Moisture and Ocean Salinity (SMOS) satellite enables a view of the sea surface from which the effects of tropical cyclones on sea surface emissivity can be measured. The emissivity at these frequencies is a function of sea surface salinity (SSS), sea surface temperature (SST), sea surface roughness, polarization, and angle of emission. If the latter four variables can be estimated, then models of the sea surface emissivity can be used to invert SSS from measured brightness temperature (TB). Actual measured TB from space also has affects due to the ionosphere and troposphere, which have to be compensated for, and components due to the galactic and cosmic background radiation those have to be removed. In this research, we study the relationships between retrieved SSS from MIRAS, and SST and precipitation collected by the NASA TMI sensor from the Tropical Rainfall Measuring Mission (TRMM) satellite during Hurricane Isaac, in August 2012. During the slower movement of the storm, just before landfall on the vicinity of the Louisiana Shelf, higher precipitation amounts were associated with lower SSS and slightly increased SST. This increased trend of SST and lower SSS under regions of high precipitation are indicative of inhibited vertical mixing. The SMOS Level 2 SSS were filtered by a stepwise process with removal of high uncertainty in TB under conditions of strong surface roughness which are known to create noise. The signature of increased SST associated with increasing precipitation was associated with decreased SSS during the storm. Although further research is required, this study shows that there is a TB signal from the sea surface beneath a tropical cyclone that provides information on roughness and salinity.

Effects of foam and wind waves on microwave ocean emission

Meissner and Wentz (M09) [4] report global WindSat measurements of wind-induced emissivity change at 6, 10, 18, 23 and 37 GHz in wind speeds up to about 50 m/s (Fig. 1). Superimposed in the figure are the SSA/SPM simulations accounting for both foam and roughness effects. The agreement between computation and measurements is generally very good. Both measurements and simulations show a monotonic increase of emissivity change with wind speed up to 50 m/s, and the rate of change seem to slow down somewhat in high winds. Fig. 2 shows the comparison of WindSat measurements and SSA/SPM simulations with the foam and roughness components displayed separately. The foam effect increases monotonically with wind stress. For the vertical polarization in the WindSat configuration (incidence angle about 53°), foam is the dominant contributor of wind-induced emissivity change. The roughness contribution is positive at 6, 10 and 18 GHz with decreasing magnitude toward higher frequency; it becomes negative at 23 and 37 GHz. The null roughness contribution occurs between 18 and 23 GHz, and this range represents the ideal frequency band for passive microwave remote sensing with minimal surface roughness contamination. For the horizontal polarization, roughness contribution dominates in all five frequencies except for a small range of wind speeds near 50 m/s at 6 GHz. For microwave frequencies less than about 10 GHz, the wind speed sensitivity of roughness contribution is less than that of the foam contribution; for higher microwave frequencies, the two contributions have similar wind speed sensitivity.